Thing

DISCLAIMER


Welcome! The goal of this blog is to share my analysis of the free, publicly available user-reported law school applicant data from Law School Numbers. Using the data from Law School Numbers is problematic for a variety of reasons (such as users misreporting their actual information, users creating fake accounts, selection bias, etc.) and if I had access to it, I'd much rather work with the data that schools themselves have on applicants. We have what we have, though. Also, while I do have some facility with the type of statistical analysis I employ in my blog posts, I am far from being a professional statistician. I am doing this solely for the purpose of providing my analysis to interested readers, getting feedback, and generating discussion. What I am not doing is prescribing courses of action for law school applicants, or pretending to actually know what goes on behind closed doors in law school admission committees' meetings. I am, however, interested in looking at the story the numbers seem to portray, and sharing that with people with similar interests. I think I'll be able to provide a lot of interesting, and perhaps even helpful, analysis here, but at the end of the day, it is up to the individual law school applicant to put together applications and application strategies tailored to his or her own hopes and goals.

Saturday, June 1, 2013

New school profiles added, thoughts on future projects

If you take a look over to the right, you'll see that in the past couple days I have added (by request) school profiles for Harvard, Columbia, and Yale.  If any of these schools interest you, please have yourself a look.

I continue to process that data and organize it, and hopefully shortly we'll be able to look at some comparisons.  I've been thinking about what I want o do with it, and here are some ideas I have come up with:

  • Looking at the approaches schools appear to have taken, both within the T14, and T14 vs. the rest, since applications started to crater a couple cycles ago.  Do numbers matter more or less?  How about everything else?  What larger trends do we see, and what school-specific approaches, if any?
  • Taking at least a superficial look at just how "epic" the predicted Epic Cycle was, and does this differ from tier to tier?
  • Broad comparisons of the importance of numbers for T14 vs. non-T14, and whether or not emphasis placed on numbers correlates with USNWR rankings.
  • I look at two basic models, one including waitlists and one excluding them, and I'm starting to see that for many schools, the boosts increase significantly in the admitted vs. rejected only model.  I'm interested in seeing if this gap correlates with the % of waitlist offers schools hand out, and seeing what we might deduce from that.
  • Taking a little more in depth look at what goes on for splitters, reverse-splitters, and ED applications at each school, possibly in order to develop a list of splitter and reverse-splitter friendly schools, which may be useful for those candidates who fall into one category or the other.  
  • Although it'll take some doing, I'd love to get a handle on scholarship awards and what factors play a role there.
  • Finally, I want to develop a page where I just explain how some of this stuff works, what I have done with the data, etc.  The question someone posted about splitters on the UC Berekely page really slapped me in the face with this necessity.

Okay, that's it for now.  I'll hopefully be adding more stuff soon, and in the meantime, I'll continue working so we can start to look at more interesting comparative analysis.  As always, I'm definitely open for suggestions and requests!

2 comments:

  1. Looking forward to this! Can't thank you enough.

    ReplyDelete
  2. Seriously, thank you so much! This is exactly what I needed, if I had time to do it myself!

    ReplyDelete